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Automatic Temperature Controls
230900S03 INSTRUMENTATION AND CONTROL FOR HVAC UK Controls Standard SECTION 230900S03 - AUTOMATIC TEMPERATURE CONTROLS PART 1 - GENERAL RELATED DOCUMENTS: Drawings and general provisions of the Contract, including General and Supplementary Conditions, General Mechanical Provisions and General Requirements, Division 1 Specification Sections apply to the work specified in this section. DESCRIPTION OF WORK: Furnish a BACnet system compatible with existing University systems. All building controllers, application controllers, and all input/output devices shall communicate using the protocols and network standards as defined by ANSI/ASHRAE Standard 135-2001, BACnet. This system shall communicate with the University of Kentucky Facility Management’s existing BACnet head-end software using BACnet/IP at the tier 1 level and BACnet/MSTP at the tier 2 level. No gateways shall be used for communication to controllers installed under section. BACnet/MSTP or BACnet/IP shall be used for all other tiers of communication. No servers shall be used for communication to controllers installed under this section. If servers are required, all hardware and operating systems must be approved by the Facilities Management Controls Engineering Manager and/or the Facilities Management Information Technology Manager. All Building Automation Devices should be located behind the University firewall, but outside of the Medical Center Firewall and on the environmental VLAN. Provide all necessary hardware and software to meet the system’s functional specifications. Provide Protocol Implementation Conformance Statement (PICS) for Windows-based control software and every controller in system, including unitary controllers. These must be in compliance with Front End systems PICS and BIBBS and attached Tridium PICS and BIBBS. -
Joey F. George Professor of MIS & Thomas L
June 16, 2009 Joey F. George Professor of MIS & Thomas L. Williams Jr. Eminent Scholar in MIS MIS Department College of Business Florida State University Tallahassee, FL 32306-1110 EDUCATION A.B. Stanford University, Stanford, California, 1979 English language and literature. M.Ed. Converse College, Spartanburg, South Carolina, 1980 Emphasis on English language and literature. Ph.D. University of California, Irvine, California, 1986. Thesis title: Computers and the centralization of decision-making in U.S. city governments. RELEVANT EXPERIENCE Professor and Thomas L. Williams Jr. Eminent Scholar in Information Systems, MIS Department, College of Business, Florida State University, August 1999 – present. University of Canterbury Visiting Erskine Fellowship, Christchurch, New Zealand, May-June, 2008 Visiting Professor, Helsinki School of Economics and Business Administration, International MBA Program, Mikkeli, Finland, July 1999. Associate Professor and Edward G. Schlieder Chair in Information Systems, E.J. Ourso College of Business Administration, Louisiana State University, August 1998-August 1999. Sprint Professor of Business Administration, College of Business, Florida State University, May 1997- August 1998. Associate Professor, IMS Dept., College of Business, Florida State University, Aug. 1993-Aug. 1998. Chair, IMS Department, College of Business, Florida State University, Dec. 1995 – Aug.1998. Assistant Professor, Department of MIS, College of Business and Public Administration, University of Arizona, August 1986-August 1993. Research Assistant, URBIS Project, Public Policy Research Organization, University of California, Irvine, Jan. 1984-March 1986. Teaching Assistant, Department of Information and Computer Science, Graduate School of Management, University of California, Irvine, Sept. 1981-Dec. 1983. Secondary English Teacher, Spartanburg Day School, Spartanburg, South Carolina, 1979-1981. -
Sagar Samtani, Ph.D. 1275 E
Sagar Samtani, Ph.D. 1275 E. 10th St, HH 4111, Bloomington, IN 47405 E-mail: [email protected] Phone Number: +1 (520)-971-4274 Website: www.sagarsamtani.com Last CV Update: July 30, 2020 __________________________________________________________________________________________________ ACADEMIC EMPLOYMENT AND POSITIONS Assistant Professor and Grant Operations and Decision Technologies, Kelley School Indiana July 2020 – Thornton Scholar of Business University Present Fellow Center for Applied Cybersecurity Research (CACR) Indiana June 2020 - University Present Assistant Professor Department of Information Systems and Decision University of August 2018 – Sciences, Muma College of Business South Florida May 2020 Adjunct Lecturer (Limited Term) Department of Management Information Systems, University of May – July Eller College of Management Arizona 2018 Research Associate, Project Lead, Artificial Intelligence Lab, Department of University of August 2014 – Scholarship-for-Service Fellow Management Information Systems Arizona May 2018 Graduate Assistant MicroAge Lab, Department of Management University of October 2013 – Information Systems, Eller College of Management Arizona May 2014 EDUCATION Doctor of Philosophy (Ph.D.) Major: Management Information Systems University of 2014-2018 Minor: Cognitive Science Arizona Masters of Science (M.S.) Management Information Systems University of 2013-2014 Arizona Bachelors of Science in Business Management Information Systems University of 2009-2013 Administration (B.S.B.A) Arizona RESEARCH INTERESTS 1. Applications: (1) Cybersecurity – cyber threat intelligence (key hacker ID, emerging threat detection, visualizations) and smart vulnerability assessment (socio-technical; automated scanning); scientific cyberinfrastructure cybersecurity (GitHub, Docker, VM images) (2) social media analytics – automated Social Intelligence (SOCINT) Open Source Intelligence (OSINT) collection/mining; (3) health analytics – motion sensor-based fall detection/prediction, activity of daily living detection; mental health 2. -
High Performance Platforms
High Performance Platforms Salvatore Orlando High Perfoamnce Computing - S. Orlando 1 Scope of Parallelism: the roadmap towards HPC • Conventional architectures are coarsely comprised of – processor, memory system, I/O • Each of these components presents significant performance bottlenecks. – It is important to understand each of these performance bottlenecks to reduce their effects • Parallelism addresses each of these components in significant ways to improve performance and reduce the bottlenecks • Applications utilize different aspects of parallelism, e.g., – data intensive applications utilize high aggregate memory bandwidth – server applications utilize high aggregate network bandwidth – scientific applications typically utilize high processing and memory system performance High Perfoamnce Computing - S. Orlando 2 Implicit Parallelism: Trends in Microprocessor Architectures • Microprocessor clock speeds have posted impressive gains over the past two decades (two to three orders of magnitude) – there are limits to this increase, also due to power consumption and heat dissipation • Higher levels of device integration have made available a large number of transistors – the issue is how best to transform these large amount of transistors into computational power • Single-core processors use these resources in multiple functional units and execute multiple instructions in the same cycle. • The precise manner in which these instructions are selected and executed provides impressive diversity in architectures. High Perfoamnce Computing - S. Orlando 3 ILP High Perfoamnce Computing - S. Orlando 4 Instruction Level Parallelism • Pipelining overlaps various stages of instruction execution to achieve performance • At a high level of abstraction, an instruction can be executed while the next one is being decoded and the next one is being fetched. • This is akin to an assembly line for manufacture of cars. -
Multiprocessing Contents
Multiprocessing Contents 1 Multiprocessing 1 1.1 Pre-history .............................................. 1 1.2 Key topics ............................................... 1 1.2.1 Processor symmetry ...................................... 1 1.2.2 Instruction and data streams ................................. 1 1.2.3 Processor coupling ...................................... 2 1.2.4 Multiprocessor Communication Architecture ......................... 2 1.3 Flynn’s taxonomy ........................................... 2 1.3.1 SISD multiprocessing ..................................... 2 1.3.2 SIMD multiprocessing .................................... 2 1.3.3 MISD multiprocessing .................................... 3 1.3.4 MIMD multiprocessing .................................... 3 1.4 See also ................................................ 3 1.5 References ............................................... 3 2 Computer multitasking 5 2.1 Multiprogramming .......................................... 5 2.2 Cooperative multitasking ....................................... 6 2.3 Preemptive multitasking ....................................... 6 2.4 Real time ............................................... 7 2.5 Multithreading ............................................ 7 2.6 Memory protection .......................................... 7 2.7 Memory swapping .......................................... 7 2.8 Programming ............................................. 7 2.9 See also ................................................ 8 2.10 References ............................................. -
Reviewer Acknowledgments
Reviewer Acknowledgments Margunn Aanestad Sameh Al-Natour Bijan Azad University of Oslo American University of Sharjah American University of Beirut Oslo, Norway Sharjah, United Arab Emirates Beirut, Lebanon Ahmed Abbasi Shoshana Altschuller Hillol Bala University of Virginia, McIntire School of Commerce Iona College Indiana University Charlottesville, Virginia New Rochelle, New York Bloomington, Indiana Alan Abrahams Catherine Anderson Sule Balkan Virginia Polytechnic Institute and State University University of Virginia Arizona State University Blacksburg, Virginia Falls Church, Virginia Tempe, Arizona Alessandro Acquisti Corey Angst Ravi Bapna Carnegie Mellon University University of Notre Dame University of Minnesota Pittsburgh, Pennsylvania Notre Dame, Indiana Minneapolis, Minnesota Ashish Agarwal Animesh Animesh Karen Barad The University of Texas at Austin McGill University University of Santa Cruz Austin, Texas Montreal, Canada Santa Cruz, California Julia Adler-Milstein Chadi Aoun Eric Barrette University of Michigan University of Technology Sydney University of Minnesota Ann Arbor, Michigan Sydney, Australia Minneapolis, Minnesota Monica Adya Sinan Aral Anitesh Barua Marquette University New York University University of Texas at Austin Milwaukee, Wisconsin New York City, New York Austin, Texas Walid Afifi Ofer Arazy Richard Baskerville University of California-Santa Barbara University of Alberta Georgia State University Santa Barbara, California Edmonton, Canada Atlanta, Georgia Ritu Agarwal Priscilla Arling Genevieve Bassellier University of Maryland Butler University McGill University College Park, Maryland Indianapolis, Indiana Montreal, Canada Leila Agha Deborah Armstrong Patrick Bateman Boston University School of Management The Florida State University Youngstown State University Boston, Massachusetts, Tallahassee, Florida Youngstown, Ohio Brad Agle Terrence August Anne Beaudry Brigham Young University University of California, San Diego Concordia University Provo, Utah San Diego, California Montreal, Canada William Agresti Robert D. -
The NIJ CONFERENCE 2011
U.S. Department of Justice Office of Justice Programs National Institute of Justice The NIJ CONFERENCE 2011 TRANSLATIONAL CRIMINOLOGY: SHAPING POLICY AND PRACTICE WITH RESEARCH U.S. Department of Justice Office of Justice Programs 810 Seventh St. N.W. Washington, DC 20531 Eric H. Holder, Jr. Attorney General Laurie O. Robinson Assistant Attorney General John H. Laub, Ph.D. Director, National Institute of Justice This and other publications and products of the National Institute of Justice can be found at: National Institute of Justice http://www.nij.gov Office of Justice Programs Innovation • Partnerships • Safer Neighborhoods http://www.ojp.usdoj.gov The NIJ CONFERENCE 2011 TRANSLATIONAL CRIMINOLOGY: SHAPING POLICY AND PRACTICE WITH RESEARCH CONFERENCE PROGRAM June 20–22, 2011 ■ Arlington, VA Watch NIJ.gov for future conference dates! The Eleventh RESCHEDULED! New Workshops Added The Crime Mapping Research Conference October 17–21, 2011 Hilton Miami Downtown The Crime Mapping Research Conference is about understanding crime, criminal justice, and public safety and their effect on, and by, places. Explore tMBUFTU SFTFBSDI mOEJOHT tQSBDUJDBM BQQMJDBUJPOT tUFDIOPMPHZ EFNPOTUSBUJPOT tQPMJDZ SFTVMUT For more information, visit http://www.nij.gov/nij/events/maps/welcome.htm Crime, Social Ills, and Place-Based Solutions Science, Significance, and Impact AUGUST 8–11, 2011, KANSAS CITY, MO A Symposium designed to bring together practitioners and researchers to enhance information-sharing and promote collaboration among the trace evidence, law enforcement, and legal communities. Featuring unique educational opportunities for trace evidence examiners. For more information, visit http://projects.nfstc.org/trace/2011/ LIST OF Ex hibits Exhibits of List National Institute of Justice Forensic Technology Center of Excellence 810 Seventh St. -
Joey F. George Professor of MIS & Thomas L
October 13, 2010 Joey F. George Professor of MIS & Thomas L. Williams Jr. Eminent Scholar in MIS Department of Management College of Business Florida State University Tallahassee, FL 32306-1110 EDUCATION A.B. Stanford University, Stanford, California, 1979 English language and literature. M.Ed. Converse College, Spartanburg, South Carolina, 1980 Emphasis on English language and literature. Ph.D. University of California, Irvine, California, 1986. Thesis title: Computers and the centralization of decision-making in U.S. city governments. RELEVANT EXPERIENCE Professor and Thomas L. Williams Jr. Eminent Scholar in Management Information Systems, College of Business, Florida State University, August 1999 – present. Senior Research Associate, Information Use Management & Policy Institute, Florida State University, 2009 – University of Canterbury Visiting Erskine Fellowship, Christchurch, New Zealand, May-June, 2008 Visiting Professor, Helsinki School of Economics and Business Administration, International MBA Program, Mikkeli, Finland, July 1999. Associate Professor and Edward G. Schlieder Chair in Information Systems, E.J. Ourso College of Business Administration, Louisiana State University, August 1998-August 1999. Sprint Professor of Business Administration, College of Business, Florida State University, May 1997- August 1998. Associate Professor, IMS Dept., College of Business, Florida State University, Aug. 1993-Aug. 1998. Chair, IMS Department, College of Business, Florida State University, Dec. 1995 – Aug.1998. Assistant Professor, Department of MIS, College of Business and Public Administration, University of Arizona, August 1986-August 1993. Research Assistant, URBIS Project, Public Policy Research Organization, University of California, Irvine, Jan. 1984-March 1986. Teaching Assistant, Department of Information and Computer Science, Graduate School of Management, University of California, Irvine, Sept. 1981-Dec. -
K1DM3 Control System Software User's Guide
K1DM3 Control System Software User's Guide William Deich University of California Observatories 07 Jan 2020 ver 3.7b Contents 1 Overview 6 1.1 Active Components of K1DM3..........................6 1.1.1 Drum....................................6 1.1.2 Swingarm..................................9 1.2 Position Summary................................. 13 1.3 Motion Controllers................................. 13 1.4 Software....................................... 14 1.4.1 Back-end Services............................. 14 1.4.2 End-User Applications........................... 15 1.5 K1DM3 Private Network.............................. 15 2 Starting, Stopping, Suspending Services 17 2.1 Starting/Stopping................................. 17 2.2 Suspending Dispatchers.............................. 19 2.3 Special No-Dock Engineering Version....................... 19 2.4 Periodic Restarts.................................. 20 3 Components, Assemblies, and Sequencers 21 3.1 Elementary Components.............................. 21 3.2 Compound Keywords............................... 22 3.3 Assemblies...................................... 22 3.4 Sequencers..................................... 23 3.5 The ACTIVATE Sequencer............................ 24 3.6 The M3AGENT Sequencer............................ 27 3.7 Monitoring Sequencer Execution......................... 27 4 Dispatcher Interfaces for Routine Operations 29 4.1 TCS Operations.................................. 31 4.2 M3AGENT..................................... 32 4.3 Hand Paddle................................... -
Computer Structures for Distributed Systems Liam
COMPUTER STRUCTURES FOR DISTRIBUTED SYSTEMS LIAM MAURICE CASEY C DOCTOR OF PHILOSOPHY UNIVERSITY OF EDINBURGH 1977. - ABSTRPCI: A building block approach to configuring large corruter. iEerns is attractive because the blocks, either primitive processors or small computers, are daily becoming cheaper and because this approach alloiis a close match of the pcwer required to the pciler supplied. This thesis addresses the design goal of an expandable system where there is no premium paid for a minimal configuration and the cost of extra units of capacity is constant. It is shoiin that a distributed system, a system of homogeneous canputers loosely coupled by a cartmunication subsystem, is likely to be the best approach to this design goal. Some consideration is given to the form of the canmunication subsystem but the rain research is directed to.ards the software organisation required to achieve efficient co-operation between the canputers constituting the distributed system. An organisation based on the domain structures of protection schenEs is found to have advantages. Hitherto dcirtain management using capabilities has been centred around systems with shared. primary memory. This is because central tables have been required to implement the capability rrechanism. A model is developed which, by restricting. the sharing of some items and providing a 'global object' managerrent scheme to cover essential sharing, enables central tables to be dispensed with and dcmain managenent to be distributed. The main goal in achieving this extension is to facilitate dynamic and efficient load sharing but the model could equally well be used to provide, in distributed systems, the protection normally associated with danains. -
Critical Success Factors in M-Learning: a Socio- Technical Perspective Vlad Krotov Abu Dhabi University, [email protected]
Communications of the Association for Information Systems Volume 36 Article 6 2-2015 Critical Success Factors in M-Learning: A Socio- Technical Perspective Vlad Krotov Abu Dhabi University, [email protected] Follow this and additional works at: https://aisel.aisnet.org/cais Recommended Citation Krotov, Vlad (2015) "Critical Success Factors in M-Learning: A Socio-Technical Perspective," Communications of the Association for Information Systems: Vol. 36 , Article 6. DOI: 10.17705/1CAIS.03606 Available at: https://aisel.aisnet.org/cais/vol36/iss1/6 This material is brought to you by the AIS Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in Communications of the Association for Information Systems by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. Critical Success Factors in M-Learning: A Socio-Technical Perspective Vlad Krotov College of Business, Abu Dhabi University, UAE [email protected] Educational institutions around the world increasingly view mobile technology as an effective platform for educating a new generation of students. Unfortunately, educational institutions often fail to achieve substantial results with their mobile-learning initiatives. Studies on m-learning have produced several recommendations about how to improve of its success. These recommendations cover a set of factors limited to people, technology, and pedagogy. This qualitative case study adopts a broader socio-technical perspective on m-learning and produces an extended list of critical success factors in m-learning. These factors fall into organization, people, pedagogy, and technology domains. I used the Abilene Christian University as the site for this study. -
Curriculum Guidelines for Undergraduate Degree Programs in Information Systems
Communications of the Association for Information Systems Volume 26 2010 Article 18 IS 2010: Curriculum Guidelines for Undergraduate Degree Programs in Information Systems Heikki Topi∗ Joseph S. Valacichy Ryan T. Wrightz Kate Kaiser∗∗ Jay F. Nunamaker, Jr.yy Janice C. Sipiorzz Gert-Jan de Vreedex ∗Bentley University, [email protected] yWashington State University zUniversity of San Francisco ∗∗Marquette University yyUniversity of Arizona zzVillanova University xUniversity of Nebraska at Omaha Copyright c 2010 by the authors. Communications of the Association for Information Systems is produced by The Berkeley Electronic Press (bepress). http://aisel.aisnet.org/cais IS 2010: Curriculum Guidelines for Undergraduate Degree Programs in Information Systems Heikki Topi; Joseph S. Valacich; Ryan T. Wright; Kate Kaiser; Jay F. Nunamaker, Jr.; Janice C. Sipior; and Gert-Jan de Vreede Abstract IS 2010 is the latest in a series of model curricula for undergraduate degrees in Information Systems. It builds on the foundation formed by this earlier work, but it is a major revision of the curriculum and incorporates several significant new characteristics. IS 2010 is the third collabo- rative effort by ACM and AIS. Both organizations have worldwide membership, and, therefore, IS 2010 includes elements that make it more universally adaptable than its predecessors. IS 2010 is not directly linked to a degree structure in any specific environment but it provides guidance regarding the core content of the curriculum that should be present everywhere and suggestions regarding possible electives and career tracks based on those. KEYWORDS: undergraduate IS curriculum, curriculum development process, computing educa- tion, model curriculum IS 2010: Curriculum Guidelines for Undergraduate Degree Programs in Information Systems Heikki Topi Bentley University [email protected] Joseph S.